Application of Neural Network Algorithm in Prediction of Linear Shaped Charge Penetration Performance
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摘要:基于难以通过型面直接准确预测切割索侵彻性能，以及神经网络算法大力发展的现状，本文对神经网络算法在切割索侵彻性能预测领域的应用情况进行了综述。在对常用神经网络计算方法进行分析后，重点对BP神经网络和卷积神经网络算法原理及其在切割索性能预测中的应用进行分析梳理和归纳总结，系统性地对两种神经网络算法的数据集处理、网络搭建模型、参数设置和优缺点进行了剖析，为切割索性能优化和智能化预测提供支撑。
Abstract:Based on the status that it is difficult to predict the penetration performance of linear shaped charge directly and accurately through the profile, and the rapid development of neural network algorithm, in this paper, the application of neural network algorithm in the field of linear shaped charge penetration performance prediction was reviewed. After analyzing the common neural network calculation methods, the analysis and summary of the principle of BP neural network and convolutional neural network algorithm, and their application in performance prediction of linear shaped charge were focused on, and the data set processing, network modeling, parameter setting, advantages and disadvantages of the two neural network algorithms were systematically analyzed. The study provides supports for performance improvement and intelligent prediction of linear shaped charge.
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